Investigating the depth of problem-solving prompts in collaborative argumentation

Tawfik, Andrew A.; Koehler, Adrie A.; Gish-Lieberman, Jaclyn J.; Gatewood, Jessica

doi:10.1080/14703297.2021.1966821

Cited by 7 publications

(2 citation statements)

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“…They found that the level of learner‐learner interaction was limited to the lower stages of IAM (e.g., sharing and comparing information). In another study, he and his colleagues used stages 1–5 of the IAM to analyse the contents of an online discussion board and explored the extent to which learners engaged in collaborative argumentation guided by both problem representation and problem‐solving processes (Tawfik et al, 2021). Myers (2021) used the IAM to code and analyse the contents of 89 discussion posts to examine learners' constructions of the meaning of citizenship in a globalized world.…”

Section: Literature Reviewmentioning

confidence: 99%

“…As described in the above studies (see, e.g., Gunawardena et al, 1997; Huang et al, 2019; Lin & Tsai, 2012; Myers, 2021; Tawfik et al, 2017, 2021; Wang et al, 2019; Zhu, 2006), many researchers have used a variety of methods to identify and analyse interactions and cognitive engagement in online learning environments. Although the aforementioned studies have made great efforts to analyse learners' interactions and cognitive engagement in online learning environments, the use of traditional manual coding methods is very time‐consuming and degrades classification performance, especially for thousands of large samples of data.…”

Section: Literature Reviewmentioning

confidence: 99%

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Understanding the evolution of cognitive engagement with interaction levels in online learning environments: Insights from learning analytics and epistemic network analysis

Guo

Zheng

2023

Computer Assisted Learning

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Background: There is a strong association between interactions and cognitive engagement, which is crucial for constructing new cognition and knowledge.Although interactions and cognitive engagement have attracted extensive attention in online learning environments, few studies have revealed the evolution of cognitive engagement with interaction levels.Objectives: The study aims to automatically identify learners' interactions and cognitive engagement and then analyse the evolution of learners' cognitive engagement with interaction levels and during different stages of online learning. Methods:The participants of the study were learners who participated in an online open course. Their text data from discussion forums on five learning themes were collected. Data were analysed using text mining and ENA.Results: Learners' cognitive engagement in online learning was related to interaction levels. As learners' online interaction levels changed from surface to deep, cognitive engagement levels changed from low to high. With the continuous occurrence of deep interactions, cognitive feedback became more complex. At the social-emotional interaction level, although learners' cognitive engagement levels began to change from low to high, complex cognitive feedback was still insufficient. In addition, the analysis of the evolution of cognitive engagement during different stages of online learning showed that learners' patterns of cognitive engagement changed significantly as the learning process continued, from initially dynamic and complex to a stable development pattern. Implications:The results of the study are of theoretical significance and practical guidance for further understanding the relationship between online interaction levels and cognitive engagement as well as the process of online collaborative knowledge exploration, construction, and even connectivity.

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Section: Literature Reviewmentioning

confidence: 99%