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Towards automatic cross-language classification of cognitive presence in online discussions
39
Citations
45
References
2020
Year
Unknown Venue
EngineeringPsycholinguisticsOnline LearningCommunicationClass Imbalance ProblemLanguage LearningCorpus LinguisticsText MiningApplied LinguisticsNatural Language ProcessingSecond Language AcquisitionComputational LinguisticsConversation AnalysisLanguage StudiesVerbal InteractionCognitive CommunicationInteractional LinguisticsComputer-mediated CommunicationOnline DiscussionsDialogue ManagementLanguage TechnologySpeech CommunicationInterpersonal CommunicationSocial ComputingRandom Forest ClassifierHuman-computer InteractionData-driven LearningLinguistics
This paper presents a study that examined automated cross-language classification of online discussion messages for the levels of cognitive presence, a key construct from the widely used Community of Inquiry (CoI) model of online learning. Specifically, we examined the classification of 1,500 Portuguese language discussion messages using a classifier trained on a corpus of the 1,747 English language discussion messages. In the study, a random forest classifier was developed using a small set of 108 validated indicators of psychological processes, linguistic coherence, and online discussion structure. The classifier obtained 67% accuracy and Cohen's κ of 0.32, showing a moderate level of inter-rater agreement above chance and the general viability of the proposed approach. Most importantly, the findings suggest that certain aspects of cognitive presence construct are highly generalizable and transfer across different languages. Finally, the paper also presents a novel method for addressing class imbalance problem using a generic algorithm heuristic technique, which provided substantial improvements over the use of imbalanced dataset. Results and practical implications are further discussed.
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