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Enregistrement W2247884604 · doi:10.1145/2809957.2809969

Ushahidi

2015· article· en· W2247884604 sur OpenAlex

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Notice bibliographique

RevueACM SIGCAS Computers and Society · 2015
Typearticle
Langueen
DomaineComputer Science
ThématiqueOnline Learning and Analytics
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSocial mediaPolitical sciencePublic relationsComputer scienceBusinessWorld Wide Web

Résumé

récupéré en direct d'OpenAlex

Computing plays a significant role in our communities from the local to the global. Computing greatly benefits social causes such as community organization, education, humanitarian relief and information access. However, many students proceed through an undergraduate degree learning of the impact that computing has in business and science, but are not made aware of the positive social impact that computing has and will continue to have. Students are taught about the impact of computing for social good as part of the author's senior Software Engineering course at MacEwan University in Edmonton, AB, Canada. In particular, the humanitarian open-source software project called Ushahidi [1] (http://www.ushahidi.com) as the platform for group projects since 2011. Ushahidi is a crisis-mapping software project that was initially developed during the 2008 Kenyan elections to allow citizens to communicate issues (e.g., violence, intimidation, and voting irregularities) that the state media was not reporting. Ushahidi has continued as an actively developed open-source project and currently has thousands of deployments worldwide including over 3000 in the U.S. alone. It has been used to help communities during numerous crises such as the Haitian earthquake, Snowmaggedon and in Syria and other "Arab Spring" countries to report violence. Last year the IPython notebook (http://www.ipython.org) as a second option for my students. Categorizing IPython as a social good project is debatable, it has broadened the experience beyond a single open-source application. Using these projects to teach about computing's social impact over the last three years is of interest for three reasons: • Open-source - Use of popular open-source humanitarian software is a compelling option for student projects so that the students' work can have a broader impact and to expose students to real-world development communities. Open-source communities also vary in their tools and collaboration style, experiences in working with the IPython and Ushahidi communities are shared. • Breadth of projects -- Several example student projects and the feedback students have given as to what they enjoyed most and least about their projects are discussed. • Effective Practices -- Use of a common virtual machine to scaffold the projects so students can get software installed and running quickly, within an hour or two, and avoid configuration problems. In each year of the last three years the author tried different approaches in having the students work on projects. He also used different pedagogical approaches, incorporating both individual and group projects, allowed students to select their own projects versus assigning them and tried different project scopes, from very specific tasks (i.e., fixing bugs) to broader, open problems such as adding new features. Finally, he mentored the students himself as well as worked with external mentors. In 2013, the author presented a poster titled "Teaching Software Engineering with a Humanitarian Open-Source Software Project" at SIGCSE. Following that poster he collaborated with the Foss2Serve project (http://foss2serve.org) and mentored faculty members at other universities in incorporating humanitarian FOSS projects in their curriculum.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: aucune
GenreSignal candidat: Méthodes · Signal consensuel: aucune
Score de désaccord entre enseignants0,924
Score d'incertitude au seuil0,375

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,032
Tête enseignante GPT0,272
Écart entre enseignants0,240 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle