16,746 research outputs found
Towards Systemic Evaluation
Problems of conventional evaluation models can be understood as an impoverished âconversationâ between realities (of non-linearity, indeterminate attributes, and ever-changing context), and models of evaluating such realities. Meanwhile, ideas of systems thinking and complexity scienceâgrouped here under the acronym STCSâstruggle to gain currency in the big âEâ world of institutionalized evaluation. Four evaluation practitioners familiar with evaluation tools associated with STCS offer perspectives on issues regarding mainstream uptake of STCS in the big âEâ world. The perspectives collectively suggest three features of practicing systemic evaluation: (i) developing value in conversing between bounded values (evaluations) and unbounded reality (evaluand), with humility; (ii) developing response-ability with evaluand stakeholders based on reflexivity, with empathy; and (iii) developing adaptive rather than mere contingent use(fulness) of STCS âtoolsâ as part of evaluation praxis, with inevitable fallibility and an orientation towards bricolage (adaptive use). The features hint towards systemic evaluation as core to a reconfigured notion of developmental evaluation
What If? The Art of Scenario Thinking for Nonprofits
Gives an overview of scenario thinking customized for a nonprofit audience. Outlines the basic phases of scenario development, and provides examples and advice for putting the process into practice. Includes an annotated bibliography of select readings
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Tensions of Data-Driven Reflection: A Case Study of Real-Time Emotional Biosensing
Biosensing displays, increasingly enrolled in emotional reflection, promise authoritative insight by presenting usersâ emotions as discrete categories. Rather than machines interpreting emotions, we sought to explore an alternative with emotional biosensing displays in which users formed their own interpretations and felt comfortable critiquing the display. So, we designed, implemented, and deployed, as a technology probe, an emotional biosensory display: Ripple is a shirt whose pattern changes color responding to the wearerâs skin conductance, which is associated with excitement. 17 participants wore Ripple over 2 days of daily life. While some participants appreciated the âphysical connectionâ Ripple provided between body and emotion, for others Ripple fostered insecurities about âhow muchâ feeling they had. Despite our design intentions, we found participants rarely questioned the displayâs relation to their feelings. Using biopolitics to speculate on Rippleâs surprising authority, we highlight ethical stakes of biosensory representations for sense of self and ways of feeling
mFish Alpha Pilot: Building a Roadmap for Effective Mobile Technology to Sustain Fisheries and Improve Fisher Livelihoods.
In June 2014 at the Our Ocean Conference in Washington, DC, United States Secretary of State John Kerry announced the ambitious goal of ending overfishing by 2020. To support that goal, the Secretary's Office of Global Partnerships launched mFish, a public-private partnership to harness the power of mobile technology to improve fisher livelihoods and increase the sustainability of fisheries around the world. The US Department of State provided a grant to 50in10 to create a pilot of mFish that would allow for the identification of behaviors and incentives that might drive more fishers to adopt novel technology. In May 2015 50in10 and Future of Fish designed a pilot to evaluate how to improve adoption of a new mobile technology platform aimed at improving fisheries data capture and fisher livelihoods. Full report
An introduction to STRIKE : STRuctured Interpretation of the Knowledge Environment
Knowledge forms a critical part of the income generation of the system and the complex environment in which actors participate in the creation of knowledge assets merits robust, eclectic consideration. STRIKE - STRuctured Interpretation of the Knowledge Environment affords an unobtrusive and systematic framework to observe, record, evaluate and articulate concrete and abstract elements of a setting, across internal and external dimensions. Inter-relationships between actor and environment are preserved.
STRIKE is supported by underlying techniques to enrich data and enhance the authenticity of its representation. Adoption of photography and videography tools provides illustrative and interpretive benefits and facilitates researcher reflexivity. This structured approach to data analysis and evaluation mitigates criticisms of methodological rigour in observational research and affords standardisation potential, germane for application in a verification or longitudinal capacity.
Advancing exploratory validation studies, the method is employed to evaluate the knowledge environments of two enterprises in the UK creative sector. These occupy a critical role in fostering entrepreneurial innovation alongside participant self-efficacy. Access Space in Sheffield and the Bristol Hackspace are committed to open software, open knowledge and open participation; sharing peer learning, creativity and socio-technical aims to address broadly similar community needs.
Drawing on Wittgensteinâs Picture Theory of Meaning, the knowledge management perspective is abstracted from the STRIKE assessment. It is argued that the tiered analytical approach which considers a breadth of dimensions enhances representation and interpretation of the knowledge environment and presents a diagnostic and prescriptive capability to actualise change. The paper concludes by evaluating framework effectiveness, findings application and future direction
A return to Teacherbot:Rethinking the development of educational technology at the University of Edinburgh
In the market discourses of technological disruption, higher education institutions have routinely been positioned in deficit models and of anachronistic approaches to teaching at odds with the types of educational futures being presented by commercial organisations. Predominantly, automation technologies in the form of artificial intelligence are being promoted as the future of teaching. In this paper, on the other hand, we explore the prospects for using non-artificial intelligence automated agents in teaching and its impact on the teacher function at the University of Edinburgh. Through engagement with teachers, staff and students at the university, this research has identified use cases for bots, in what spaces they would be situated, and how they would supplement the teacher function. This paper argues that a community-driven approach combined with a sociomaterial conceptualisation can generate a shift from market discourses and to collaborative development of educational technologies
"Challenge Current Practice and Assumptions! Make waves!!â : What Works Scotland Collaborative Learning Event 23 & 24 February 2016 Queens Hotel, Perth
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Human-Centered Technologies for Inclusive Collection and Analysis of Public-Generated Data
The meteoric rise in the popularity of public engagement platforms such as social media, customer review websites, and public input solicitation efforts strives for establishing an inclusive environment for the public to share their thoughts, ideas, opinions, and experiences. Many decisions made at a personal, local, or national scale are often fueled by data generated by the public. As such, inclusive collection, analysis, sensemaking, and utilization of pubic-generated data are crucial to support the exercise of successful decision-making processes. However, people often struggle to engage, participate, and share their opinions due to inaccessibility, the rigidity of traditional public engagement methods, and the lack of options to provide opinions while avoiding potential confrontations. Concurrently, data analysts and decision-makers grapple with the challenges of analyzing, sensemaking, and making informed decisions based on public-generated data, which includes high dimensionality, ambiguity present in human language, and a lack of tools and techniques catered to their needs. Novel technological interventions are therefore necessary to enable the public to share their input without barriers and allow decision-makers to capture, forage, peruse, and sublimate public-generated data into concrete and actionable insights.
The goal of this dissertation is to demonstrate how human-centered approaches involve the stakeholders in the design, development, and evaluation of tools and techniques that can lead to inclusive, effective, and efficient approaches to public-generated data collection and analysis to support informed decision-making. To that end, in this dissertation, I first addressed the challenges of empowering the public to share their opinions by exploring two major opinion-sharing avenues --- social media and public consultation. To learn more about people\u27s social media experiences and challenges, I built two technology probes and conducted a qualitative exploratory study with 16 participants. This study is followed up by exploring the challenges of inclusive participation during public consultations such as town halls. Based on a formative study with 66 participants and 20 organizers, I designed and developed CommunityClick to enable reticent share their opinions silently and anonymously during town halls. Equipped with the knowledge and experiences from these works, I designed, developed, and evaluated technologies and methods to facilitate and accelerate informed data-driven decision-making based on increased public-generated data. Based on interviews with 14 analysts and decision-makers in the civic domain, I built a visual analytics system CommunityClick that can facilitate public input analysis by surfacing hidden insights, people\u27s reflections, and priorities. Leveraging the lessons learned during this work, I created a visual text analytics system that supports serendipitous discovery and balanced analysis of textual data to help make informed decisions.
In this work, I contribute an understanding of how people collect and analyze public-generated data to fuel their decisions when they have increased exposure to alternative avenues for opinion-sharing. Through a series of human-centered studies, I highlight the challenges that inhibit inclusivity in opinion sharing and shortcomings of existing methods that prevent decision-makers to account for comprehensive public input that includes marginalized or unpopular opinions. To address these challenges, I designed, developed, and evaluated a collection of interactive systems including CommunityClick, CommunityPulse, and Serendyze. Through a rigorous set of evaluation strategies which include creativity sessions, controlled lab studies, in-the-wild deployment, and field experiments, I involved stakeholders to assess the effectiveness and utility of the built systems. Through the empirical evidence from these studies, I demonstrate how alternative designs for social media could enhance people\u27s social media experiences and enable them to make new connections with others to share opinions. In addition, I show how CommunityClick can be utilized to enable reticent attendees during public consultation to share their opinions while avoiding unwanted confrontation and allowing organizers to capture and account for silent feedback. I highlight how CommunityPulse allowed analysts and decision-makers to examine public input from multiple angles for an accelerated analysis and more informed decision-making. Furthermore, I demonstrate how supporting serendipitous discovery and balanced analysis using Serendyze can lead to more informed data-driven decision-making. I conclude the dissertation with a discussion on future avenues to expand this research including the facilitation of multi-user collaborative analysis, integration of multi-modal signals in the analysis of public-generated data, and potential adoption strategies for decision-support systems designed for inclusive collection and analysis of public-generated data
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