Specifying computer-supported collaboration scripts

Collaboration scripts are activity programs which aim to foster collaborative learning by structuring interaction between learners. Computer-supported collaboration scripts generally suffer from the problem of being restrained to a specific learning platform and learning context. A standardization of collaboration scripts first requires a specification of collaboration scripts that integrates multiple perspectives from computer science, education and psychology. So far, only few and limited attempts at such specifications have been made. This paper aims to consolidate and expand these approaches in light of recent findings and to propose a generic framework for the specification of collaboration scripts. The framework enables a description of collaboration scripts using a small number of components (participants, activities, roles, resources and groups) and mechanisms (task distribution, group formation and sequencing)

Four facets of a process modeling facilitator

Business process modeling as a practice and research field has received great attention in recent years. However, while related artifacts such as models, tools or grammars have substantially matured, comparatively little is known about the activities that are conducted as part of the actual act of process modeling. Especially the key role of the modeling facilitator has not been researched to date. In this paper, we propose a new theory-grounded, conceptual framework describing four facets (the driving engineer, the driving artist, the catalyzing engineer, and the catalyzing artist) that can be used by a facilitator. These facets with behavioral styles have been empirically explored via in-depth interviews and additional questionnaires with experienced process analysts. We develop a proposal for an emerging theory for describing, investigating, and explaining different behaviors associated with Business Process Modeling Facilitation. This theory is an important sensitizing vehicle for examining processes and outcomes from process modeling endeavors

Analyzing collaborative learning processes automatically

In this article we describe the emerging area of text classification research focused on the problem of collaborative learning process analysis both from a broad perspective and more specifically in terms of a publicly available tool set called TagHelper tools. Analyzing the variety of pedagogically valuable facets of learners’ interactions is a time consuming and effortful process. Improving automated analyses of such highly valued processes of collaborative learning by adapting and applying recent text classification technologies would make it a less arduous task to obtain insights from corpus data. This endeavor also holds the potential for enabling substantially improved on-line instruction both by providing teachers and facilitators with reports about the groups they are moderating and by triggering context sensitive collaborative learning support on an as-needed basis. In this article, we report on an interdisciplinary research project, which has been investigating the effectiveness of applying text classification technology to a large CSCL corpus that has been analyzed by human coders using a theory-based multidimensional coding scheme. We report promising results and include an in-depth discussion of important issues such as reliability, validity, and efficiency that should be considered when deciding on the appropriateness of adopting a new technology such as TagHelper tools. One major technical contribution of this work is a demonstration that an important piece of the work towards making text classification technology effective for this purpose is designing and building linguistic pattern detectors, otherwise known as features, that can be extracted reliably from texts and that have high predictive power for the categories of discourse actions that the CSCL community is interested in

A Combined Representation Learning Approach for Better Job and Skill Recommendation

Job recommendation is an important task for the modern recruitment industry. An excellent job recommender system not only enables to recommend a higher paying job which is maximally aligned with the skill-set of the current job, but also suggests to acquire few additional skills which are required to assume the new position. In this work, we created three types of information net- works from the historical job data: (i) job transition network, (ii) job-skill network, and (iii) skill co-occurrence network. We provide a representation learning model which can utilize the information from all three networks to jointly learn the representation of the jobs and skills in the shared k-dimensional latent space. In our experiments, we show that by jointly learning the representation for the jobs and skills, our model provides better recommendation for both jobs and skills. Additionally, we also show some case studies which validate our claims

Needle-Moving Community Collaboratives: A Promising Approach to Addressing America's Biggest Challenges

Communities face powerful challenges -- a high-school dropout epidemic, youth unemployment, teen pregnancy -- that require powerful solutions. In a climate of increasingly constrained resources, those solutions must help communities to achieve more with less. A new kind of community collaborative -- an approach that aspires to significant community-wide progress by enlisting all sectors to work together toward a common goal -- offers enormous promise to bring about broader, more lasting change across the nation

Knowledge Cartography for Controversies: The Iraq Debate

In analysing controversies and debates—which would include reviewing a literature in order to plan research, or assessing intelligence to formulate policy—there is no one worldview which can be mapped, for instance as a single, coherent concept map. The cartographic challenge is to show which facts are agreed and contested, and the different kinds of narrative links that use facts as evidence to define the nature of the problem, what to do about it, and why. We will use the debate around the invasion of Iraq to demonstrate the methodology of using a knowledge mapping tool to extract key ideas from source materials, in order to classify and connect them within and across a set of perspectives of interest to the analyst. We reflect on the value that this approach adds, and how it relates to other argument mapping approaches

Trends in LN-embedding practices at Waikato Institute of Technology (Wintec) in 2019

In this report, we describe the trends in literacy-embedding practices of level-2 and level-3 tutors who worked in vocational contexts at Waikato Institute of Technology (Wintec), and who completed the New Zealand Certificate in Adult Literacy and Numeracy Education (NZCALNE[Voc]) in 2019. We analysed 19 observations, following constructivist grounded theory methodology (Charmaz, 2014), to produce 1302 descriptive labels that highlight literacy and numeracy practices integrated into tutors’ teaching intentionally pursued in a collaborative and mentored training process. Of the initial 12 categories, we conflated the mapping of LN course demands and identifying learners’ LN needs to arrive at a final 11. We then used these categories in an axial analysis (Saldaňa, 2013), categorising the 1302 labels as binaries (i.e. if the label was related to the category, 1 was coded; if not 0 [zero]). The matrix of 14322 ratings of 1s and 0s was then analysed. We calculated the frequency of 1s by category. We argued that the axial analysis allowed us to develop a more holistic perspective which showed how the 1302 labels were configured in relation to the 11 categories of analysis. We concluded that the 11 categories represented key aspects of vocational teaching and training emphasising that LN-embedding practices have to be seamlessly integrated into general pedagogical approaches. A key construct for new tutors is to shape their understanding of seamlessly integrated versus bolted-on LN practices. Our recommendations remain within the whole-of-organisation perspective proposed in the 2017-2018 report (Greyling, 2019)

Free and open source software development of IT systems

IT system development, integration, deployment, and administration benefit significantly from free and open source software (FOSS) tools and services. Affordability has been a compelling reason for adopting FOSS in computing curricula and equipping computing labs with support infrastructure. Using FOSS systems and services, however, is just the first step in taking advantage of how FOSS development principles and practices can impact student learning in IT degree programs. Above all, FOSS development of IT systems requires changes to how students, instructors, and other contributors work collaboratively and openly and get involved and invested in project activities. In this paper I examine the challenges to engage students in FOSS development projects proposed by real clients. A six-week course project revealed problems with adopting FOSS development and collaboration across different activities and roles that student team members have assumed. Despite these problems, students have showed a genuine and strong interest in gaining more practice with FOSS development. FOSS development teaching was further refined in two other courses to learn about adequate teaching strategies and the competencies that students achieve when they participate in FOSS development of IT systems