An Introduction to the Integrated Community-Engaged Learning and Ethical Reflection Framework (I-CELER)

Cultivating ethical Science, Technology, Engineering, and Mathematics researchers and practitioners requires movement beyond reducing ethical instruction to the rational exploration of moral quandaries via case studies and into the complexity of the ethical issues that students will encounter within their careers. We designed the Integrated Community-Engaged Learning and Ethical Reflection (I-CELER) framework as a means to promote the ethical becoming of future STEM practitioners. This paper provides a synthesis of and rationale for I-CELER for promoting ethical becoming based on scholarly literature from various social science fields, including social anthropology, moral development, and psychology. This paper proceeds in five parts. First, we introduce the state of the art of engineering ethics instruction; argue for the need of a lens that we describe as ethical becoming; and then detail the Specific Aims of the I-CELER approach. Second, we outline the three interrelated components of the project intervention. Third, we detail our convergent mixed methods research design, including its qualitative and quantitative counterparts. Fourth, we provide a brief description of what a course modified to the I-CELER approach might look like. Finally, we close by detailing the potential impact of this study in light of existing ethics education research within STEM

Analytic Metaphysics versus Naturalized Metaphysics: The Relevance of Applied Ontology

The relevance of analytic metaphysics has come under criticism: Ladyman & Ross, for instance, have suggested do discontinue the field. French & McKenzie have argued in defense of analytic metaphysics that it develops tools that could turn out to be useful for philosophy of physics. In this article, we show first that this heuristic defense of metaphysics can be extended to the scientific field of applied ontology, which uses constructs from analytic metaphysics. Second, we elaborate on a parallel by French & McKenzie between mathematics and metaphysics to show that the whole field of analytic metaphysics, being useful not only for philosophy but also for science, should continue to exist as a largely autonomous field

Computing Competencies for Undergraduate Data Science Curricula: ACM Data Science Task Force

At the August 2017 ACM Education Council meeting, a task force was formed to explore a process to add to the broad, interdisciplinary conversation on data science, with an articulation of the role of computing discipline-specific contributions to this emerging field. Specifically, the task force would seek to define what the computing/computational contributions are to this new field, and provide guidance on computing-specific competencies in data science for departments offering such programs of study at the undergraduate level. There are many stakeholders in the discussion of data science – these include colleges and universities that (hope to) offer data science programs, employers who hope to hire a workforce with knowledge and experience in data science, as well as individuals and professional societies representing the fields of computing, statistics, machine learning, computational biology, computational social sciences, digital humanities, and others. There is a shared desire to form a broad interdisciplinary definition of data science and to develop curriculum guidance for degree programs in data science. This volume builds upon the important work of other groups who have published guidelines for data science education. There is a need to acknowledge the definition and description of the individual contributions to this interdisciplinary field. For instance, those interested in the business context for these concepts generally use the term “analytics”; in some cases, the abbreviation DSA appears, meaning Data Science and Analytics. This volume is the third draft articulation of computing-focused competencies for data science. It recognizes the inherent interdisciplinarity of data science and situates computing-specific competencies within the broader interdisciplinary space

The role of pedagogical tools in active learning: a case for sense-making

Evidence from the research literature indicates that both audience response systems (ARS) and guided inquiry worksheets (GIW) can lead to greater student engagement, learning, and equity in the STEM classroom. We compare the use of these two tools in large enrollment STEM courses delivered in different contexts, one in biology and one in engineering. The instructors studied utilized each of the active learning tools differently. In the biology course, ARS questions were used mainly to check in with students and assess if they were correctly interpreting and understanding worksheet questions. The engineering course presented ARS questions that afforded students the opportunity to apply learned concepts to new scenarios towards improving students conceptual understanding. In the biology course, the GIWs were primarily used in stand-alone activities, and most of the information necessary for students to answer the questions was contained within the worksheet in a context that aligned with a disciplinary model. In the engineering course, the instructor intended for students to reference their lecture notes and rely on their conceptual knowledge of fundamental principles from the previous ARS class session in order to successfully answer the GIW questions. However, while their specific implementation structures and practices differed, both instructors used these tools to build towards the same basic disciplinary thinking and sense-making processes of conceptual reasoning, quantitative reasoning, and metacognitive thinking.Comment: 20 pages, 5 figure

Innovating Pedagogy 2017: Exploring new forms of teaching, learning and assessment, to guide educators and policy makers. Open University Innovation Report 6

This series of reports explores new forms of teaching, learning and assessment for an interactive world, to guide teachers and policy makers in productive innovation. This sixth report proposes ten innovations that are already in currency but have not yet had a profound influence on education. To produce it, a group of academics at the Institute of Educational Technology in The Open University collaborated with researchers from the Learning In a NetworKed Society (LINKS) Israeli Center of Research Excellence (I-CORE). Themes: • Big-data inquiry: thinking with data • Learners making science • Navigating post-truth societies • Immersive learning • Learning with internal values • Student-led analytics • Intergroup empathy • Humanistic knowledge-building communities • Open Textbooks • Spaced Learnin

Engineering - young people want to be informed

Young people in developed nations recognise the contribution that science and technology make to society and acknowledge their importance now and in the future, yet few view their study as leading to interesting careers. Some countries are taking action to raise interest in science, technologies, engineering and mathematics and increase the number of students studying these subjects. One of the barriers to young people pursuing engineering is their limited or distorted perception of it - they associate it only with building and fixing things. Young people rarely encounter engineers, unlike other professionals, engineering has little or no advocacy in the media and there are few opportunities to experience engineering. Many of the pupils surveyed at the start of Engineering the Future, a three year EPSRC-funded project, wrote “don’t know what engineering is” and/or “would like more information”. This paper reports on work with researchers, policy makers and practitioners in Scotland to develop a sustainable model of activities and interactions that develops pupils’ understanding of the nature of engineering, embeds experiences of engineering within the school classroom and curriculum and promotes engineering as a career. After learning about engineering through the activities the pupils’ perceptions had improved. Almost all considered it important that young people know about engineering, because it is an essential part of everyday life and, in the words of one pupil - “If we know more about it, our minds wouldn’t stay closed to it. We would maybe take it up.

Comparative analysis of knowledge representation and reasoning requirements across a range of life sciences textbooks.

BackgroundUsing knowledge representation for biomedical projects is now commonplace. In previous work, we represented the knowledge found in a college-level biology textbook in a fashion useful for answering questions. We showed that embedding the knowledge representation and question-answering abilities in an electronic textbook helped to engage student interest and improve learning. A natural question that arises from this success, and this paper's primary focus, is whether a similar approach is applicable across a range of life science textbooks. To answer that question, we considered four different textbooks, ranging from a below-introductory college biology text to an advanced, graduate-level neuroscience textbook. For these textbooks, we investigated the following questions: (1) To what extent is knowledge shared between the different textbooks? (2) To what extent can the same upper ontology be used to represent the knowledge found in different textbooks? (3) To what extent can the questions of interest for a range of textbooks be answered by using the same reasoning mechanisms?ResultsOur existing modeling and reasoning methods apply especially well both to a textbook that is comparable in level to the text studied in our previous work (i.e., an introductory-level text) and to a textbook at a lower level, suggesting potential for a high degree of portability. Even for the overlapping knowledge found across the textbooks, the level of detail covered in each textbook was different, which requires that the representations must be customized for each textbook. We also found that for advanced textbooks, representing models and scientific reasoning processes was particularly important.ConclusionsWith some additional work, our representation methodology would be applicable to a range of textbooks. The requirements for knowledge representation are common across textbooks, suggesting that a shared semantic infrastructure for the life sciences is feasible. Because our representation overlaps heavily with those already being used for biomedical ontologies, this work suggests a natural pathway to include such representations as part of the life sciences curriculum at different grade levels

CREATIVITY IN ENTREPRENEURSHIP EDUCATION

This paper uses social cognitive theory to investigate entrepreneurial intent among participants in graduate entrepreneurship programs. To the best of our knowledge, the paper is the first to investigate the importance of creativity in entrepreneurship education and theoretical models of entrepreneurial intentions. Specifically, we test whether students creative potential is related to their intention to engage in entrepreneurship. Theoretically derived hypotheses are tested using multiple and ordinal regression analyses. We find that high scores on a creativity test and prior entrepreneurial experiences were positively associated with entrepreneurial intentions, whereas perception of risks had a negative influence. Our theoretical predictors of entreprenurial intention received strong support, indicating that creativity should be considered in models of entrepreneurial intentions. Yet, the use of intentions as dependent variable has its know weaknesses in that we might not distinguish between 'dreamers' and 'doers'. The findings indicate that exercises in creativity can be used to raise entrepreneurial intentions of students in entrepreneurship education. Heterogeneity in creative styles among students also points to the problems of a ‘one-size-fits-all’ approach to entrepreneurship education.Entrepreneurship education; intentions; creativity

Increasing STEM Competence in Urban, High Poverty Elementary School Populations

Enhancing STEM competence (e.g., interests, knowledge, skills, and dispositions) among urban, high poverty, elementary school populations in the United States (U.S.) is and remains a growing national concern, especially since Science, Technology, Engineering and Mathematics (STEM) competence is and will continue to be a necessary requisite for gainful employment in the future, according to workforce development experts. In an attempt to address this gap, many urban elementary schools have begun to offer STEM-related programs to increase STEM learning at an early age. STEM competence (interest, knowledge, skills, and dispositions), however, remains low. This paper results in a matrix used to analyze children\u27s fictional literary selections and a model that argues that elementary teachers, as the first point of contact with young students, can affect STEM competence. By adopting a more culturally responsive pedagogy that attends to the 21st Century Learning Skills and the Next Generation Science Standards, teachers can choose literature that serves to excite and reinforce STEM learning