Self-efficacy and behavior patterns of learners using a real-time collaboration system developed for group programming

In order to promote the practice of co-creation, a real-time collaboration (RTC) version of the popular block-based programming (BBP) learning environment, MIT App Inventor (MAI), was proposed and implemented. RTC overcomes challenges related to non-collocated group work, thus lowering barriers to cross-region and multi-user collaborative software development. An empirical study probed into the differential impact on self-efficacy and collaborative behavior of learners in the environment depending upon their disciplinary background. The study serves as an example of the use of learning analytics to explore the frequent behavior patterns of adult learners, in this case specifically while performing BBP in MAI integrated with RTC. This study compares behavior patterns that are collaborative or individual that occurred on the platform, and investigates the effects of collaboration on learners working within the RTC depending on whether they were CS-majors or not. We highlight advantages of the new MAI design during multi-user programming in the online RTC based on the connections between the interface design and BBP as illustrated by two significant behavior patterns found in this instructional experiment. First, the multi-user programming in the RTC allowed multiple tasks to happen at the same time, which promoted engagement in joint behavior. For example, one user arranged components in the interface design while another dragged blocks to complete the program. Second, this study confirmed that the Computer Programming Self-Efficacy (CPSE) was similar for individual and multi-user programming overall. The CPSE of the homogeneous CS-major groups engaged in programming within the RTC was higher than that of the homogeneous non-CS-major groups and heterogeneous groups. There was no significant difference between the CPSE of the homogenous non-CS group and the CPSE of the heterogeneous groups, regardless of whether they were engaged in individual programming or collaborative programming within their groups. The results of the study support the value of engaging with MAI collaboratively, especially for CS-majors, and suggest directions for future work in RTC design.

Global biomes and ecozones – Conceptual and spatial communalities and discrepancies

Various facets of global changes and related problems and challenges are asking for sound impact assessments and corresponding coping strategies. The human impact on nature is a major driver of biodiversity loss and restricted ecosystem functioning and services. Assessing such global changes is often done by using biomes as benchmarks. However, even if the wording and terminology seem common sense (‘tropical rain forest’, ‘steppe’, ‘boreal forest’) global biome units and maps deviate in many ways. This is well justified by their individual intention, expert opinions, disciplinary background, and methodology of creation. A closer look reveals linkages between spatial accordance and common origin in climate classifications and maps. Their original influence, however, is rarely evident. In consequence, it is difficult if not impossible for users to realize and understand differences in these global maps. Furthermore, it is difficult to accept the fact that there is no common standard for global biomes. Even more surprising is the fact that some approaches are uncritically taken for common sense and are perpetuated over decades. This study aims to review established global biome concepts. Regions that are consistently assigned to comparable types of biomes shall be detected and also regions where ambiguity exists. For this purpose, we shortly review the history of existing concepts and the generic relations between them. Biomes, ecozones and climate classifications are considered. We digitized the most prominent biome classifications. Spatial match and mismatch between concepts were analyzed globally. We detect areas of spatial agreement and regions with ambiguous classifications. A clustering approach including 287 individual biomes originating from 12 established global biome concepts and their classifications/units revealed 12 terrestrial biome clusters among which 8 can be assigned to terrestrial ecological units. One cluster on ice caps adds to this. And finally, 3 clusters represent rather transition zones (ecotones), high mountain plateaus or are of minor areal extent. The spatial arrangement of these emerging clusters is displayed on a global map. Additionally, regions of uncertainty related to class assignment were identified. Those primarily occur in the vicinity of mountainous regions. The findings of this study should be seen as a work in progress and as a basis for further optimization of global biome concepts.

A Tour of Gang Ethnographies: Key Themes in Contemporary Studies around the World

This chapter offers a review of recently published gang ethnographies across four continents. Historically rooted in the United States, today the gang phenomena as well as gang ethnographies are subjected to processes of globalization. Europe, Latin America, and increasingly the Global South are emerging as important field sites for ethnographic research. Contemporary unprecedented levels of international migration, displacement, and deportation of people shape current gang ethnographies and have led to reconfigurations of century-old debates. Global forces also push the traditional boundaries of ethnographic field site across nation-state borders and into the online world. In the past two decades, the nationality, gender, as well as the disciplinary background of gang ethnographers has also dramatically diversified. Nonetheless, the visibility of gang ethnographies is still highly dependent of an ethnographers’ nationality and linguistic skills. Here Anglophone researchers as well as ethnographers associated with countries that are more affluent and universities still have a clear advantage over the majority of scholars of the Global South.

“During the interview, the interpreter will provide a faithful translation.” The potentials and pitfalls of researchinginterpreting in immigration, asylum, and police settings: methodology and research paradigms

This article presents a bibliometrical survey of an extensive corpus of research on interpreting in immigration, asylum andpolice settings. The article takes stock ofpast research andpoints towards questionsforfurther research. The corpus of relevant literature is grouped according to the authors’ disciplinary background, and examined on the basis of a bibliometrical analysis with respect to the authors’ affiliation, type(s) ofpublication, date(s) of publication, methodology, and predominant paradigms and topics. The survey also investigates the different analytical (mainly discourse analytical) approaches that have been used to analyse these kind of interpreter-mediated interviews

Teaching Mechatronic System Modeling: A Fifteen-Year Journey

Most innovations happen at the intersections of disciplines. New products get designed through synergistic integration of multi-disciplinary concepts. For example, in today’s automobiles purely mechanical systems have been replaced by “by-wire” devices that are software controlled, lighter, more efficient, and reliable. While engineering disciplines are merging seamlessly in real world products, academic silos are mostly still intact. At University of Detroit Mercy, we have broken down some silos by launching the Robotics and Mechatronics Systems Engineering major. Mechatronic Systems Modeling is a mandatory course in this major. This course uses a technique of power flow called bond graphs to model mechatronic systems. This technique is not discipline specific and students with different disciplinary background can easily understand and master it. Recently, the use of Simscape, a MATLAB/Simulink tool for physical system modeling has also been added to this course. The use of these two tools in complex system modeling tasks helps students develop an understanding of engineering system behavior by moving beyond the narrow boundaries of individual disciplines. This paper describes the course content and structure, the modeling methods, selected student projects, some of the lessons learned, and several offshoot activities that have resulted from this course.

Initiating scientific collaborations across career levels and disciplines – a network analysis on behavioral data

Collaborations are essential in research, especially in answering increasingly complex questions that require integrating knowledge from different disciplines and that engage multiple stakeholders. Fostering such collaboration between newcomers and established researchers helps keep scientific communities alive while opening the way to innovation. But this is a challenge for scientific communities, especially as little is known about the onset of such collaborations. Prior social network research suggests that face-to-face interaction at scientific events as well as both network-driven selection patterns (reciprocity and transitivity) and patterns of active selection of specific others (homophily / heterophily) may be important. Learning science research implies, moreover, that selecting appropriate collaboration partners may require group awareness. In a field study at two scientific events on technology-enhanced learning (Alpine Rendez-Vous 2011 and 2013) including N = 5736 relations between 287 researchers, we investigated how researchers selected future collaboration partners, looking specifically at the role of career level, disciplinary background, and selection patterns. Face-to-face contact was measured using RFID devices. Additionally, a group awareness intervention was experimentally varied. Data was analyzed using RSiena and meta-analyses. The results showed that transitivity, reciprocity and contact duration are relevant for the identification of new potential collaboration partners. PhD students were less often chosen as new potential collaboration partners, and researchers with a background in Information Technology selected fewer new potential collaboration partners. However, group awareness support balanced this disciplinary difference. Theoretical, methodological, and practical implications of these findings are discussed.

Assessing the State of Coupled Social-Ecological Modeling in Support of Ecosystem Based Fisheries Management in the United States

There has been a proliferation of coupled social-ecological systems (SES) models created and published in recent years. However, the degree of coupling between natural and social systems varies widely across the different coupled models and is often a function of the disciplinary background of the team conducting the research. This manuscript examines models developed for and used by NOAA Fisheries in support of Ecosystem Based Fisheries Management (EBFM) in the United States. It provides resource managers and interdisciplinary scientists insights on the strengths and weaknesses of the most commonly used SES models: end-to-end models, conceptual models, bioeconomic models, management strategy evaluations (MSEs), fisher behavior models, integrated social vulnerability models, and regional economic impact models. These model types are not unique to the literature, but allow us to differentiate between one-way coupled models – where outputs from one model are inputs into a second model of another discipline with no feedback to the first model, and two-way coupled models – where there are linkages between the natural and social system models. For a model to provide useful strategic or tactical advice, it should only be coupled to the degree necessary to understand the important dynamics/responses of the system and to create management-relevant performance metrics or potential risks from an (in)action. However, one key finding is to not wait to integrate! This paper highlights the importance of “when” the coupling happens, as timing affects the ability to fully address management questions and multi-sectoral usage conflicts that consider the full SES for EBFM or ecosystem based management (EBM) more generally.

Housing Discourse: Historical development, epistemological gap and sociological modeling

<p>Housing issue is essentially major social issue. Even though housing is vital for individual life and social life, the attention given to its theorization and epistemological framework is neglected. Different disciplines and scholars from different disciplinary background have been carrying out housing study. The misplacement of housing study and social relegation of housing per se triggered this theoretical review of housing discourses. Housing study needs to have self-governing epistemological ground and housing research should be framed with its grand theories. Housing is a key social need that strongholds the foundational essence of social fabric. So far housing studies did not understand housing discourses as a central sociological agenda. Isolation of housing issue from major sociological concerns misplaced housing study thereby affected epistemological and methodological advancement of housing knowledge. Therefore, housing study call for grand theory that potentially governs all aspects of housing issues. Housing is a social phenomenon which can be expressed in terms of processes, behaviors, development and structures. Housing problems are attributed to different social dynamics and structural challenges which enforce households to behave in different ways to cope with the problems. These issues are basically sociological concerns which enable us to scaffold housing study with sociological theories. </p>

A breeding pool of ideas: Analyzing interdisciplinary collaborations at the Complex Systems Summer School

Interdisciplinary research is essential for the study of complex systems, and so there is a growing need to understand the factors that facilitate collaboration across diverse fields of inquiry. In this exploratory study, we examine the composition of self-organized project groups and the structure of collaboration networks at the Santa Fe Institute’s Complex Systems Summer School. Using data from all iterations of the summer school from 2005 to 2019, comprising 823 participants and 322 projects, we investigate the factors that contribute to group composition. We first test for homophily with respect to individual-level attributes, finding that group composition is largely consistent with random mixing based on gender, career position, institutional prestige, and country of study. However, we find some evidence of homophilic preference in group composition based on disciplinary background. We then conduct analyses at the level of group projects, finding that project topics from the Social and Behavioral Sciences are over-represented. This could be due to a higher level of baseline interest in, or knowledge of, social and behavioral sciences, or the common application of methods from the natural sciences to problems in the social sciences. Consequently, future research should explore this discrepancy further and examine whether it can be mitigated through policies aimed at making topics in other disciplines more accessible or appealing for collaboration.