MASSIVE OPEN ONLINE COURSES AS E-BRICKS FOR SMART CITIES
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Open Educational Resources and Massive Open Online Courses as e-bricks for Smart Cities Authors: Carmen Holotescu, Gabriela Grosseck, Laura Malita Nowadays when more than half of the world's population lives in urban areas, when information and (mobile) communication technologies are real catalysts for innovations in all domains, there are a lot of studies and debates related to how our cities should become "Smart Cities", "Smarter Cities" or "Future Cities", in order to improve life quality and to reduce costs. The paper starts with a literature research related to definitions for the "Smart City" term and to the needed steps / action plans / strategies for such a transformation. The new citizens will have vital roles in building smart cities; they should be hyperconnected, creative, entrepreneurs, also they should actively participate and collaborate in the cities activities and decisions. The paper will explore: - How Open Educational Resources and Massive Open Online Courses can support the citizens engagement, learning and participation, also new skills and competencies development? - How the authorities can collaborate with universities and researchers to develop specific OER and to organize such courses? Which new policies are neeeded? - Which features should be offered by MOOCs platforms and how such courses can be facilitated? - What lessons can be learned from current projects targeting these issues? References: Bacsich, P., & Pepler, G. (2013). Learner Use of Online Content.Teaching and Learning Online: New Models of Learning for a Connected World, 2, 75. Buchem, I., & P?rez-Sanagust?n, M. (2013). Personal Learning Environments in Smart Cities: Current Approaches and Future Scenarios. http://openeducationeuropa.eu/sites/default/files/asset/In-depth_35_1.pdf Department for Business, Innovation and Skills, London. (2013). The Maturing of the MOOC. https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/240193/13-1173-maturing-of-the-mooc.pdf Falconer, I., McGill, L., Littlejohn, A., Boursinou, E., & Punie, Y. (2013). Overview and Analysis of Practices with Open Educational Resources in Adult Education in Europe. ftp://ftp.jrc.es/pub/EURdoc/JRC85471.pdf
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it