Online Learning Community Building: a Case Study in China
Bibliographic record
Abstract
Much attention has been paid to online community building in recent years due to its much acclaimed potential of enhancing knowledge construction in the Information Age. However, there is a lack of empirical studies on the process of how online learning community influence knowledge construction in particular and enhance the quality of learning in general. This paper is devoted to a case study of a popular language learning community in China (www.HJenglish.com) by drawing upon the metaphor online community is a miniature society, and thus an informal learning model is presented. In the light of the SOCIETY metaphor, virtual space and real social context are converged to facilitate the understanding the complex process of online learning. A text-based analysis of observable online activities and discourse was performed and a follow-up online questionnaire was performed to further explore how online learners conduct their voluntary learning activities and in the meantime shape the cultural environment which in turn facilitates meaningful learning. This paper concludes that to fully grasp the learning process in an online community, three aspects, namely social presence, affective supports and cognitive development, should be taken into consideration. Key words: online learning community, social presence, constructionism, CALL Resume: L’attention pretee a la construction de la communaute d’apprentissage sur ligne dans les dernieres annees est due a son potentiel beaucoup proclame de renforcer la construction du savoir a l’âge d’information. Cependant, il y a lacune dans les recherches empiriques sur le fait que comment la communaute d’apprentissage sur ligne influence la construction du savoir et ameliore en general la qualite d’apprentissage. L’article present entreprend une etude de cas d’une communaute d’apprentissage de langue populaire en Chine (www.HJenglish.com), en utilisant la metaphore « La communaute sur ligne est une societe en miniature », et presente ainsi un modele d’apprentissage informel. A la lumiere de la metaphore de « societe », l’espace virtuel et le contexte social reel conjurent a faciliter la comprehension du processus complexe de l’apprentissage sur ligne. Une analyse, basee sur le texte, des activites et discours observables sur ligne et une enquete suivante sur ligne sont effectuees pour explorer profondement comment les apprenants sur ligne conduisent leurs activites d’apprentissage volontaires et, en meme temps, faconner l’environnement culturel qui a son tour facilite l’apprentissage. L’auteur en arrive a conclure que, pour comprendre pleinement le processus d’apprentissage dans une communaute sur ligne, trois aspects, a savoir la presence sociale, le support affectif et le developpement cognitif, doivent etre pris en consideration. Mots-Cles: communaute d’apprentissage sur ligne, presence sociale, constructuralisme, CALL
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".