Proceedings of the 21st Annual Conference on Information Technology Education
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
It gives us immense pleasure to welcome you to the 21st Annual Conference of the Special Interest Group in IT Education (SIGITE 2020) being held virtually during a unique time in our lives. It has been quite a year already. The world around us continues to face an unprecedented time with the pandemic and years of structural racism. We greatly appreciate your continuing understanding and flexibility as the situation demanded. We also wanted to extend our sincere gratitude to all the authors and the more than one hundred reviewers for engaging with SIGITE 2020 despite the stresses of the pandemic in everyone's lives. We are thrilled to inform you that the conference received 118 high quality submissions from authors representing 95 different universities from around the world including USA (90%), India, Italy, Thailand, Austria, Canada, Chile, China, Hungary, Indonesia, Nigeria, Philippines, Romania, Tunisia, UAE, Ireland, UK, and Mexico. We are also excited to have three outstanding keynote speakers for the conference - Mr. Steve Kaniewski, President and CEO of Valmont Industries, who used to be the SVP/CIO of the same company; Dr Maria Telleria, Canvas Co-Founder and CTO; and Dr. Lecia Barker, NCWIT Senior Research Scientist and Associate Professor at University of Colorado Boulder. The final conference program has 57 completed research papers, 21 posters/extended abstracts, 5 big idea talks, 6 Work in Progress research papers, 3 panels, 4 workshops and 4 teacher experience track talks. All in all a truly representative collection of work in the IT Education and affiliated domains. Putting together SIGITE2020 was a team effort primarily led by the conference and program cochairs and included a number of graduate student volunteers helping with the logistics of the conference. We thank the authors for providing the content of the program. We appreciate our employer, the University of Nebraska at Omaha and in particular the College of Information Science & Technology for supporting us and providing in-kind material and people support for the conference. We express our sincere gratitude to our generous local supporters who agreed to continue supporting the conference even after Covid-19 budget cuts in their organizations. We encourage you to thank these supporters/exhibitors since their contribution allowed a dramatic reduction in our registration rates for all delegates to the virtual conference. Specifically: platinum supporters: Nebraska Tech Collaborative and Union Pacific Railroad; Silver supporters: Conagra Foods and Blue Cross Blue Shield of Nebraska; Academic Supporter Heider School of Business at Creighton University; and other supporters include First National Bank of Omaha, Metropolitan Community College and Prospect Press. Finally we would extend our thanks to the ACM staff for giving us rapid support as the situation changed.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,002 |
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.
score_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