Мрежови модел на практическо обучение в магистърската програма по мениджмънт на услуги и организации за неформално образование
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
Студията представя резултатите от партиципативен action research, който цели пилотното изследване на мрежови модел за практическо обучение. Дизайнът на обучението, който комбинира онлайн и офлайн среди, ресурси, подкрепи и комуникация, се основава на концептуалната синергия между социалния конструктивизъм, конективизма и теорията за актьорската мрежа. Холистичният подход създава широки възможности за студентите магистри да функционират като проактивни архитекти на своето собствено професионално развитие и практически опит чрез интегрирането на формално, неформално и аформално практическо учене и обучение. Резултатите показват, че ефективността на мрежовия дизайн зависи от комплекс от ключови фактори – човешки и материални. Сред тях основополагаща роля играе ангажираността на академичната общност в устойчива крос-секторна работа в мрежа. Библиогарфия: Камп, А., Сътрудничество в образованието: уроците на теорията за „актьорската“ мрежа. − В: Към трансформиращо образование. С., 2012. Anderson, T., & Dron, J. (2011). Three generations of distance education pedagogy. International Review of Research in Open and Distance Learning, 12(3). − http://www.irrodl.org/index.php/irrodl/article/view/890/1663 − 8.01.2014. Bruns, A. (2008). Blogs, Wikipedia, Second Life, and Beyond: From Production to Produsage. New York: Peter Lang, 418 pp. Davis, C., Edmunds, E., & Kelly-Bateman, V. (2008). Connectivism. In M. Orey (Ed.), Emerging perspectives on learning, teaching, and technology. − http://projects.coe.uga.edu/epltt − 08.01.2014. Downes, S. (2007). An Introduction to Connective Knowledge. In Hug, T. (ed.): Media, Knowledge & Education - Exploring new Spaces, Relations and Dynamics in Digital Media Ecologies. Proceedings of the International Conference, Innsbruck: Innsbruck University Press. Retrieved August 14, 2011. − http://www.downes.ca/post/33034 − 8.01.2014. Dowens, S. (2012). Connectivism and Connective Knowledge. Essays on meaning and learning networks. − http://online.upaep.mx/campusTest/ebooks/CONECTIVEKNOW LEDGE.pdf − 8.01.2014. Dron, J., & Anderson, T. (2007). Collectives, networks and groups in social software for e-learning. Paper presented at the Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, Quebec. − www.editlib.org/index.cfm/fi les/paper_26726.pdf − 8.01.2014. Latour, 1993, Latour, B. (1987). Science in Action: How to Follow Scientists and Engineers Through Society.Milton Keynes: Open University Press.). Merriam-Webster Dictionary. − http://www.merriam-webster.com/dictionary/professionalism) − 8.01.2014. Phillips, S. (2002). Social capital, local networks and community development. In C. Rakodi & T. Lloyd-Jones (Eds.), Urban livelihoods: A people-centred approach to reducing poverty. London: Earthscan, pp.133–150. Siemens, G. (2005a). Connectivism: Learning as Network-Creation. ASTD: Learning Circuits. − http://www.astd.org/LC/2005/1105_seimens.htm − 8.01.2014. Siemens, G. (2005b). Connectivism: A learning theory for the digital age. International Journal of Instructional Technology and Distance Learning, 2(1).− http://www.itdl.org/journal/jan_05/article01.htm − 8.01.2014. Sociology Dictionary. − http://sociology.about.com/od/P_Index/g/Professionalization.htm − 8.01.2014.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 | 0.010 |
| Meta-epidemiology (narrow) | 0.008 | 0.009 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.005 | 0.017 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.012 | 0.003 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.036 | 0.025 |
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