How Online Learners Build Cognitive Presence: Implications from a Machine Learning Approach

Within the last year, the number of students who participate in online learning platforms has exploded. The transition to online platforms has moved discussion out of the classroom and onto digital spaces. To support this transition we aim to create a model which can help teachers and teaching assistants understand how the discourse of learners in discussion forums evolve through multiple phases of cognitive presence over time.To this end, we use cutting-edge natural language processing techniques and apply machine-learning algorithms to build a model that can predict the cognitive presence phase of posts based on the community of inquiry framework.

[1]  Leonidas J. Guibas,et al.  Taskonomy: Disentangling Task Transfer Learning , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[2]  George Siemens,et al.  A Novel Model of Cognitive Presence Assessment Using Automated Learning Analytics Methods , 2017 .

[3]  Noureddine Elouazizi Point-of-View Mining and Cognitive Presence in MOOCs: A (Computational) Linguistics Perspective , 2014, EMNLP 2014.

[4]  Maija Aksela,et al.  Dynamics of the Community of Inquiry (CoI) within a Massive Open Online Course (MOOC) for In-Service Teachers in Environmental Education , 2018 .

[5]  Lukasz Kaiser,et al.  Attention is All you Need , 2017, NIPS.

[6]  Nasser Giacaman,et al.  Towards automated analysis of cognitive presence in MOOC discussions: a manual classification study , 2020, LAK.

[7]  S. Manca,et al.  Learning from decades of online distance education: MOOCs and the Community of Inquiry framework , 2017 .

[8]  Ming-Wei Chang,et al.  BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , 2019, NAACL.

[9]  Bernt Schiele,et al.  Meta-Transfer Learning for Few-Shot Learning , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[10]  D. Garrison,et al.  Critical thinking, cognitive presence, and computer conferencing in distance education , 2001 .

[11]  Aubteen Darabi,et al.  Cognitive presence in asynchronous online learning: a comparison of four discussion strategies , 2011, J. Comput. Assist. Learn..

[12]  Frank Hutter,et al.  Decoupled Weight Decay Regularization , 2017, ICLR.

[13]  Jeffrey Dean,et al.  Efficient Estimation of Word Representations in Vector Space , 2013, ICLR.