Metalearning-Informed Competence in Children: Implications for Responsible Brain-Inspired Artificial Intelligence

This paper offers a novel conceptual framework comprising four essential cognitive mechanisms that operate concurrently and collaboratively to enable metalearning (knowledge and regulation of learning) strategy implementation in young children. A roadmap incorporating the core mechanisms and the associated strategies is presented as an explanation of the developing brain's remarkable cross-context learning competence. The tetrad of fundamental complementary processes is chosen to collectively represent the bare-bones metalearning architecture that can be extended to artificial intelligence (AI) systems emulating brain-like learning and problem-solving skills. Utilizing the metalearning-enabled young mind as a model for brain-inspired computing, this work further discusses important implications for morally grounded AI.Comment: 27 pages, 3 figure

Unconstrained design: improving multitasking with in-vehicle information systems through enhanced situation awareness

In the age of information, in-vehicle multitasking is inevitable. The popularity of the automobile in combination with the demands of everyday life presents a demand to do more than simply focus on the road. Situation Awareness (SA) is a theory that allows designers to understand how operators interact in dynamic, complex environments. Unconstrained Design is proposed as a way of enhancing multitasking performance in-vehicle. This paper presents an experimental investigation into human-machine interface concepts that aim to support drivers to multitask in-vehicle when frequent task switching is required. Two SA-based approaches were investigated, one which focussed on supporting preparation for a Non-Driving Related Activity (NDRA), and one which focussed on supporting the Driving Related Activity (DRA) when an NDRA is active. While multitasking, Contextual Cueing, using a Head-up Display, produced significant reductions in NDRA response time while an auditory lane keeping aid increased the amount of time a driver spent in the central region of a lane. This provides evidence to suggest that using SA and Unconstrained Design as a philosophy for the design of IVIS that supports drivers’ ability to multitask in-vehicle, could lead to task performance improvements.Jaguar Land Rove

Applying science of learning in education: Infusing psychological science into the curriculum

The field of specialization known as the science of learning is not, in fact, one field. Science of learning is a term that serves as an umbrella for many lines of research, theory, and application. A term with an even wider reach is Learning Sciences (Sawyer, 2006). The present book represents a sliver, albeit a substantial one, of the scholarship on the science of learning and its application in educational settings (Science of Instruction, Mayer 2011). Although much, but not all, of what is presented in this book is focused on learning in college and university settings, teachers of all academic levels may find the recommendations made by chapter authors of service. The overarching theme of this book is on the interplay between the science of learning, the science of instruction, and the science of assessment (Mayer, 2011). The science of learning is a systematic and empirical approach to understanding how people learn. More formally, Mayer (2011) defined the science of learning as the “scientific study of how people learn” (p. 3). The science of instruction (Mayer 2011), informed in part by the science of learning, is also on display throughout the book. Mayer defined the science of instruction as the “scientific study of how to help people learn” (p. 3). Finally, the assessment of student learning (e.g., learning, remembering, transferring knowledge) during and after instruction helps us determine the effectiveness of our instructional methods. Mayer defined the science of assessment as the “scientific study of how to determine what people know” (p.3). Most of the research and applications presented in this book are completed within a science of learning framework. Researchers first conducted research to understand how people learn in certain controlled contexts (i.e., in the laboratory) and then they, or others, began to consider how these understandings could be applied in educational settings. Work on the cognitive load theory of learning, which is discussed in depth in several chapters of this book (e.g., Chew; Lee and Kalyuga; Mayer; Renkl), provides an excellent example that documents how science of learning has led to valuable work on the science of instruction. Most of the work described in this book is based on theory and research in cognitive psychology. We might have selected other topics (and, thus, other authors) that have their research base in behavior analysis, computational modeling and computer science, neuroscience, etc. We made the selections we did because the work of our authors ties together nicely and seemed to us to have direct applicability in academic settings

Automatic assessment of text-based responses in post-secondary education: A systematic review

Text-based open-ended questions in academic formative and summative assessments help students become deep learners and prepare them to understand concepts for a subsequent conceptual assessment. However, grading text-based questions, especially in large courses, is tedious and time-consuming for instructors. Text processing models continue progressing with the rapid development of Artificial Intelligence (AI) tools and Natural Language Processing (NLP) algorithms. Especially after breakthroughs in Large Language Models (LLM), there is immense potential to automate rapid assessment and feedback of text-based responses in education. This systematic review adopts a scientific and reproducible literature search strategy based on the PRISMA process using explicit inclusion and exclusion criteria to study text-based automatic assessment systems in post-secondary education, screening 838 papers and synthesizing 93 studies. To understand how text-based automatic assessment systems have been developed and applied in education in recent years, three research questions are considered. All included studies are summarized and categorized according to a proposed comprehensive framework, including the input and output of the system, research motivation, and research outcomes, aiming to answer the research questions accordingly. Additionally, the typical studies of automated assessment systems, research methods, and application domains in these studies are investigated and summarized. This systematic review provides an overview of recent educational applications of text-based assessment systems for understanding the latest AI/NLP developments assisting in text-based assessments in higher education. Findings will particularly benefit researchers and educators incorporating LLMs such as ChatGPT into their educational activities.Comment: 27 pages, 4 figures, 6 table

Leveraging Multimodal Learning Analytics to Understand How Humans Learn with Emerging Technologies

Major education and training challenges are plaguing the United States in preparing the next generation of the future workforce to meet the demands of the 21st Century. Several calls have been released to improve education programs to ensure learners are acquiring 21st century knowledge, skills, and abilities (KSAs). As we embark on the digital and automation ages of the 21st century, it is essential that we move away from traditional education programs that define and measure KSAs as static constructs (e.g., standardized assessments) with little consideration of the actual real-time deployment of these processes, missing critical information on the degree to which learners are acquiring and applying 21st century KSAs. The objective of this dissertation is to use 1 book chapter and 2 journal articles to illustrate the value in leveraging emerging technologies and multimodal trace data to define and measure scientific thinking, reflection, and self-regulated learning--core 21st century skills, across contexts, domains, tasks, and populations (e.g., medical versus undergraduates versus middle-school students). Chapters 2-4 of this dissertation provide evidence of ways to leverage multimodal trace data guided by theoretical perspectives in cognitive and learning sciences, with a special focus in self-regulated learning, to assess the extent to which learners engaged in scientific thinking, reflection, and self-regulated learning during learning activities with emerging technologies. Overall, results from these chapters illustrate that it is necessary to utilize methods that capture learning processes as they unfold during learning activities that are guided by theoretical perspectives in self-regulated learning. Findings from this research hold significant broader impacts for addressing the education and training challenges in the United States by collecting multimodal trace data over the course of learning to not only detect and identify how learners are developing KSAs such as scientific thinking, reflection, and self-regulated learning, but where these data could be fed into an intelligent and adaptive system to repurpose it back to trainers, teachers, instructors, and learners for just-in-time interventions and individualized feedback. The intellectual merit of this dissertation focuses predominantly on the importance of utilizing rich streams of multimodal trace data that are mapped onto different theoretical perspectives on how humans self-regulate across tasks like clinical reasoning, scientific thinking, and reflection with emerging technologies such as a game-based learning environment called Crystal Island. Discussion is incorporated around ways to leverage multimodal trace data on undergraduate, middle-school, and medical student populations across a range of tasks including learning about microbiology to problem solving with a game-based learning environment called Crystal Island and clinically reasoning about diagnoses across emerging technologies

Innovative Learning Environments in STEM Higher Education

As explored in this open access book, higher education in STEM fields is influenced by many factors, including education research, government and school policies, financial considerations, technology limitations, and acceptance of innovations by faculty and students. In 2018, Drs. Ryoo and Winkelmann explored the opportunities, challenges, and future research initiatives of innovative learning environments (ILEs) in higher education STEM disciplines in their pioneering project: eXploring the Future of Innovative Learning Environments (X-FILEs). Workshop participants evaluated four main ILE categories: personalized and adaptive learning, multimodal learning formats, cross/extended reality (XR), and artificial intelligence (AI) and machine learning (ML). This open access book gathers the perspectives expressed during the X-FILEs workshop and its follow-up activities. It is designed to help inform education policy makers, researchers, developers, and practitioners about the adoption and implementation of ILEs in higher education

Complicating creativity: student insights into the production of a literary anthology

2017 Fall.Includes bibliographical references.This study originated from my curiosity about the link between critical thinking and creativity and my desire to foster both in my high school visual art and English language arts students and classes. Using qualitative data--student interviews and field notes, and an examination of literature focused primarily on critical thinking and creativity--I attempt several things: 1. to understand and define how critical thinking and creativity interact or inform one another in practice; 2. to reconcile historical and contemporary models of creativity with my own observations, experiences, and student responses; and, 3. to identify and recommend classroom practices and approaches that best promote critical thinking and creativity in students across modes of literacy. I also propose, and ultimately challenge, a conceptual theory for promoting creativity. I refer to this concept as "metacreativity," which is an active process of considering the factors that affect the creative process during creative acts in order to "optimize" the process itself. As a teacher and faculty advisor for a high school literary and art magazine, I conducted classroom research via initial and exit interviews with three students in my Writing for Literary Publication class. I also maintained field notes from my observations of student discussions and their written evaluations of student writing and art pieces submitted to the magazine, as well as discussions with colleagues and mentors. Findings suggest that the curricular student-published literary anthology supports students' intellectual and creative growth in unique ways and offers tremendous opportunities for students to claim ownership of their learning. A review of the literature revealed numerous incongruities in the ways creativity is studied, understood, and defined, as well as the sophisticated yet often ambiguous nature of creative processes. I conclude that most historical models or paradigms for understanding creativity are inadequate and/or problematic for either understanding or fostering creative thinking. I contend that a much more holistic approach to both examining and promoting creativity is necessary. More research is needed, but ultimately, I argue that the curricular model employed in Writing for Literary Publication is one of the most effective ways to promote critical and creative thinking in students