Cross-disciplinary Competences Research Articles

Evaluating research-oriented teaching: a new instrument to assess university students’ research competences

Several concepts have been developed to implement research-oriented teaching in higher education in the last 15 years. The definition of research competences, however, has received minor attention so far. Some approaches to modeling research competences describe these competences along the research process but either focus on a specific academic discipline and/or specific facets or offer no empirical verification for cross-disciplinary approaches. We have developed a new approach to model research competences across various academic disciplines in form of a competence model—the RMRC-K-model. This model comprises five dimensions: skills in reviewing the state of research, methodological skills, skills in reflecting on research findings, communication skills, and content knowledge. In this study, we present an instrument (R-Comp) developed on the basis of this cross-disciplinary competence model. The factorial structure of the R-Comp was examined with data from 391 university students in three groups, either enrolled in a Bachelor’s degree, Master’s degree, or a PhD program. The sample represented various academic disciplines. Results from confirmatory factor analyses supported the hypothesized structure of the R-Comp for the five dimensions in accordance with the RMRC-K-model. Additionally, results provided evidence for a more detailed differentiation of all dimensions with sub-dimensions reflecting theorized facets of the model. Both Cronbach’s α and construct reliability H indicated overall good reliability. Despite limitations to this study, there is some first evidence of a valid and reliable assessment of student research competences.

A natural language-based approach for a semi-automatic data mart design and ETL generation

Data warehousing projects still face challenges in the various phases of the development life cycle. In particular, the success of the design phase, the focus of this paper, is hindered by the cross-disciplinary competences it requires. This paper presents a natural language-based method for the design of data mart schemas. Compared to existing approaches, our method has three main advantages: first, it facilitates requirements specification through a template covering all concepts of the decision-making process while providing for the acquisition of analytical requirements written in a structured natural language format. Second, it supports requirement validation with respect to a data source used in the ETL process. Third, it provides for a semi-automatic generation of conceptual data mart schemas that are directly mapped onto the data source; this mapping assists the definition of ETL procedures. The performance of the proposed method is illustrated through a software prototype used in an empirical comparison of our method with top-down methods.

Collaboration between Industry and Engineering Education

At present the industry needs an engineer to master cross-disciplinary competencies and general skills in terms of outcome based education, basis for continuing education and development. Every engineer does not have to master all of these skills and competencies, since sharing knowledge and networking are ways to both deepen and widen personal knowledge into a competent team or network. The educational factors for the student studying engineering technologies lie in the practical R&D processes. The students were assigned to the on job training in the actual R&D in the practical industrial sides. The frameworks that can be deployed across various institutes foe fostering creativity and innovation. The framework envisages various path ways such as research, corporate, socio managerial and entrepreneurial. The frame work would have the facility to develop a network of various educational institutes especially to share the learning in this area. Education is always a relevant issue for those of us in the electronics industry. It affects not only our technological status in the world but also the availability and competency of qualified graduates to fill job openings. If you aren't paying attention to education, now is the time to give it some time. The industry and academia both support the creation of more industry-college partnerships, internships, and industry participation. Meanwhile, STEM (science, technology, engineering and math) education in the K through 16 grades is ongoing, but more needs to be done to attract more students to fill the pipeline to employment in engineering.

The Role of Dietitians in Providing Guidance: On the Use of Natural Health Products

Dietitians are experts on nutrition, and yet much uncertainty remains about their readiness and capacity to address a rapidly evolving marketplace of novel foods, nutrients, and nutrient-like substances (i.e., natural health products [NHPs]), which are available to consumers. In 2011, we conducted a qualitative examination of current thinking on the scope of practice, as well as barriers to and facilitators of dietitians' role as experts in providing guidance on NHP use. We sought rich descriptions of existing and future dietetic competencies with NHPs. We therefore conducted six focus groups. Participants were 18 dietitians practising in rural settings and 21 practising in urban settings of Atlantic Canada. Themes identified included people, products, and information; future education and training underlay these themes. The "food first" philosophy of dietetics practice was a primary convergent theme, the consensus being that NHPs can be used for select populations, lifestyles, and health conditions. The less food-related the NHP, the more divergent opinions were on specific competencies and scope of practice; focus group participants often referred to the importance of "doing no harm" and evidence-based practice. Dietitians' achievement of competency in providing guidance on NHPs will require core, consistent, and cross-disciplinary information and competencies, as well as enhanced integrative practice models.

Developing Cross-Disciplinary Competencies through College Algebra

To argue for the importance of an integrative approach to learning in introductory STEM (Science, Technology, Engineering and Mathematics) and other courses, we present a case study of a project incorporating cross-curricular skills in a college algebra course. We analyze student work on the project and responses to surveys, and find the assignment affects positively students’ mastery of specific quantitative skills, perceptions of learning, civic awareness, and sense of relevance of mathematical study. We use the analysis to suggest guidelines for designing other activities aiming to teach the whole student in introductory courses.

The Application of LiDAR to Assessment of Rooftop Solar Photovoltaic Deployment Potential in a Municipal District Unit

A methodology is provided for the application of Light Detection and Ranging (LiDAR) to automated solar photovoltaic (PV) deployment analysis on the regional scale. Challenges in urban information extraction and management for solar PV deployment assessment are determined and quantitative solutions are offered. This paper provides the following contributions: (i) a methodology that is consistent with recommendations from existing literature advocating the integration of cross-disciplinary competences in remote sensing (RS), GIS, computer vision and urban environmental studies; (ii) a robust methodology that can work with low-resolution, incomprehensive data and reconstruct vegetation and building separately, but concurrently; (iii) recommendations for future generation of software. A case study is presented as an example of the methodology. Experience from the case study such as the trade-off between time consumption and data quality are discussed to highlight a need for connectivity between demographic information, electrical engineering schemes and GIS and a typical factor of solar useful roofs extracted per method. Finally, conclusions are developed to provide a final methodology to extract the most useful information from the lowest resolution and least comprehensive data to provide solar electric assessments over large areas, which can be adapted anywhere in the world.

Supporting statistical literacy: What do culturally relevant/realistic tasks show us about the nature of pupil engagement with statistics?

The Portuguese curriculum has recently moved away from a focus on individual subject disciplines towards the development of cross-disciplinary competencies for civic life, including the development of statistical literacy in application to everyday problems. Students are encouraged to draw on their own interests to collect and organize data sets in support of intra- and inter-disciplinary problem solving, reasoning and communication. In this paper we investigate this conception of the development of statistical literacy and its relation to ‘real life’ by exploring the talk of three pairs of working-class Portuguese students engaged in a task that was considered to be culturally relevant and realistic, and hence supportive of the development of civic competencies. We analyse what the nature of their talk indicates about the role of identities and dispositions in the way they approach statistics and their application in the real world. We suggest that differences between how each pair of students engages with the tasks illustrate the importance of individual experience and identity in accessing important statistical literacy.

The New Pedagogy of Open Content: Bringing Together Production, Knowledge, Development, and Learning

The fast growing Open Content movement has profound consequences for pedagogical approaches to learning. This paper will explore the use of Open Content in higher education, including training for scientists and scholars at large, and consider its pedagogic implications. Relevance of these issues is expected to grow in the near future, involving the ability of scholars to cope with the increased need to access, search through, and fruitfully draw knowledge from data, especially for teams where cross-disciplinary competences are required to analyse, evaluate, and exchange data across a variety of research fields.

NEWS AND COMMENT ON REVENT DEVELOPMENTS FROM AROUND THE WORLD : World summit on information society set to take place under ITU’s leadership

It is critical for “catching-up” countries to narrow innovation gaps with developed countries by developing emerging industries. This research introduces a data-mining based method to systematically assess the national innovation gap that is specifically for emerging industries. The method examines the five key attributes of emerging industries, including the ownership of platform technologies, globalization intention, international knowledge position, university-industry linkage, and cross-disciplinary technology development. In particular, this method combines data-mining with experts' knowledge to build patent-training examples, and then uses a support vector machine-based classifier to single out all high-quality patents for each innovation attribute. Based on the selected high-quality patents, the authors utilize a factorial design analysis to systematically evaluate the innovation gap between countries. This method can significantly reduce measurement bias of traditional single patent indicators. In addition, it also can robustly adjust measuring weights in response to the specifics of each innovation attribute, while traditional multi-attribute evaluation methods cannot. As a result, this research empirically shows that China' industrial robot sector has apparent innovation gaps compared to developed economies, specifically in university-industry linkage, cross-disciplinary competence, and globalization intention, and this calls for the attention of policy makers and industrial experts.